Widespread use of computers, processors, and controllers results in the generation of large amounts of data. In financial, manufacturing, and computer networking industries, to name a few, data regarding transactions, operations and performance of devices may be gathered and typically written to databases. Accordingly, data may be analyzed by data analysis tools to provide bases for production planning, operations analysis and/or improvement, and fine tuning of devices or machines.
An application for data analysis can be used to analyze gathered data. The application may be tailored to the type of data gathered. For example, discrete data, such as for example, event counts, may be analyzed in one particular way by an application. As another example, continuous-valued data, for example, event durations, may be analyzed in another way, and perhaps by a different application altogether.
An application may be adapted to produce output in the form of a probability or probabilities, for example, “there is a 75% chance of rain tomorrow.” Another application may produce output in the form of a prediction of a value, with an associated confidence for the value. A value may be in the form of a number, for example, $23.95, or may be in the form of a class, for example, severity or impact of an event. There may be, for example, three classes: mild, medium, or severe.
Typically separate applications are utilized for data analysis according to the type, size, or other characteristic of the data set. It would be useful to have a tool that can select, apply, and combine different data analysis tools to produce output according to a variety of output options.